Comparing Azure Data Factory with Funnel and Weld


What is Azure Data Factory
Pros
- 90+ built-in connectors (Azure SQL, Cosmos DB, SAP, Oracle, Salesforce, etc.) and support for custom REST endpoints.
- Visual pipeline orchestration with debug, parameterization, and Git integration for CI/CD.
- Hybrid data integration via Self-hosted Integration Runtime for on-premises sources.
- Integration with Azure Synapse, Databricks, and Azure Functions for flexible transformation and compute.
Cons
- Complex pricing: charges per pipeline activity, per DIU for data flows, and for data movement across regions.
- UI can be slow when working with large pipelines; error messages are often generic, requiring deeper investigation.
- Steeper learning curve for advanced features (e.g., mapping data flows with Spark under the hood).
Azure Data Factory Documentation:
What I like about Azure Data Factory
ADF’s visual pipeline authoring and integration with other Azure services (Databricks, Synapse) make it easy to build end-to-end data workflows without managing infrastructure.
What I dislike about Azure Data Factory
Pricing is multifaceted (per activity run, data movement, SSIS integration), which can be hard to forecast. Debugging pipeline errors often requires sifting through activity logs.
What is Funnel
Pros
- Great interface
- Requires little technical expertise
- Straightforward dashboard
- More than 500 data connectors
- Great onboarding and training
Cons
- Expensive and complex, especially for smaller businesses
- Limited advanced analytics
- Reporting features could be more robust
- Limited to marketing use cases
- Steep and long learning curve
A reviewer on G2:
What I like about Funnel
We use Funnel mostly for ingesting data into BigQuery. Using the native connectors is significantly more efficient than building a direct connection to the relevant APIs, particularly for Facebook / Meta data.
What I dislike about Funnel
Recently the price of the platform has gone up. Although it is still priced competitively vs its alternatives.
What is Weld
Pros
- Premium quality connectors and reliability
- User-friendly and easy to set up
- AI assistant
- Very competitive and easy-to-understand pricing model
- Reverse ETL option
- Lineage, orchestration, and workflow features
- Advanced transformation and SQL modeling capabilities
- Ability to handle large datasets and near real-time data sync
- Combines data from a wide range of sources for a single source of truth
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
A reviewer on G2 said:
What I like about Weld
First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.
What I dislike about Weld
Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.
Feature-by-Feature Comparison
Ease of Use & Interface
Azure Data Factory
ADF’s UI provides a canvas for building pipelines and data flows. Basic data movement is intuitive, but advanced mapping data flows (visual Spark transformations) require understanding Spark concepts. Integration with Git makes collaboration easier.
Funnel
Funnel.io is designed to be easy to use, with a straightforward dashboard that requires little technical expertise, making it accessible for marketers.
Pricing & Affordability
Azure Data Factory
ADF charges per pipeline activity (at least $0.25/activity), per DIU-hour for data flows, plus data movement costs (e.g., $0.25/GB). Estimating costs can be tricky due to these components, but pay-as-you-go avoids upfront fees.
Funnel
Funnel.io's pricing can be complex and expensive, especially for smaller businesses, which might find it challenging to justify the cost for their needs. The platform operates on a flexpoints system, a type of consumption-based pricing, which can make it difficult for users to predict their monthly costs accurately.
Feature Set
Azure Data Factory
Features include: pipeline orchestration, mapping data flows (visual Spark jobs), hybrid integration via self-hosted runtime, triggers (schedule, event, tumbling window), monitoring & alerting, and integration with Azure Monitor. Also supports SSIS lift-and-shift for on-prem ETL workloads.
Funnel
The platform offers over 500 data connectors and great onboarding and training, but its analytics capabilities may be limited for users needing more advanced features.
Flexibility & Customization
Azure Data Factory
ADF allows custom .NET activities, Azure Functions, and Databricks notebooks within pipelines. It supports parameterized templates, branching, and custom Azure ML scoring steps. However, customization often requires familiarity with other Azure services.
Funnel
Funnel.io is limited to marketing use cases and may lack the flexibility needed for more comprehensive data operations, but is effective within its niche.
Summary of Azure Data Factory vs Funnel vs Weld
Weld | Azure Data Factory | Funnel | |
---|---|---|---|
Connectors | 200+ | 90+ | 500+ |
Price | $79 / No data volume limits | Pay per activity run + data movement; starts ~$0.25 per DIU-hour for data flows | $1.08 / flexpoint per month |
Free tier | No | Yes | Yes |
Location | EU | Azure Global (multi-region) | SE |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | Yes |
On-Premise | No | No | No |
Orchestration | Yes | Yes | No |
Lineage | Yes | Yes | No |
Version control | Yes | Yes | No |
Load data to and from Excel | Yes | Yes | No |
Load data to and from Google Sheets | Yes | No | No |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | No | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | No |
G2 Rating | 4.8 | 4.4 | 4.5 |
Conclusion
You’re comparing Azure Data Factory, Funnel, Weld. Each of these tools has its own strengths:
- Azure Data Factory: features include: pipeline orchestration, mapping data flows (visual spark jobs), hybrid integration via self-hosted runtime, triggers (schedule, event, tumbling window), monitoring & alerting, and integration with azure monitor. also supports ssis lift-and-shift for on-prem etl workloads. . adf charges per pipeline activity (at least $0.25/activity), per diu-hour for data flows, plus data movement costs (e.g., $0.25/gb). estimating costs can be tricky due to these components, but pay-as-you-go avoids upfront fees. .
- Funnel: the platform offers over 500 data connectors and great onboarding and training, but its analytics capabilities may be limited for users needing more advanced features.. funnel.io's pricing can be complex and expensive, especially for smaller businesses, which might find it challenging to justify the cost for their needs. the platform operates on a flexpoints system, a type of consumption-based pricing, which can make it difficult for users to predict their monthly costs accurately..
- Weld: weld integrates elt, data transformations, and reverse etl all within one platform. it also provides advanced features such as data lineage, orchestration, workflow management, and an ai assistant, which helps in automating repetitive tasks and optimizing workflows.. weld offers a straightforward and competitive pricing model, starting at $99 for 2 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..